Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Design Database for Quantitative Trait Loci (QTL) Data Warehouse, Data Mining, and Meta-Analysis

  • Protocol
  • First Online:
Quantitative Trait Loci (QTL)

Part of the book series: Methods in Molecular Biology ((MIMB,volume 871))

Abstract

A database can be used to warehouse quantitative trait loci (QTL) data from multiple sources for comparison, genomic data mining, and meta-analysis. A robust database design involves sound data structure logistics, meaningful data transformations, normalization, and proper user interface designs. This chapter starts with a brief review of relational database basics and concentrates on issues associated with curation of QTL data into a relational database, with emphasis on the principles of data normalization and structure optimization. In addition, some simple examples of QTL data mining and meta-analysis are included. These examples are provided to help readers better understand the potential and importance of sound database design.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Korstanje R, Paigen B (2002) From QTL to gene: the harvest begins. Nat Genet 31:235–236

    Article  PubMed  CAS  Google Scholar 

  2. Rat Genome Database, QTL. HU http://rgd.mcw.edu/objectSearch/qtlQuery.jsp UH. Accessed 21 Feb 2012

  3. The Jackson Laboratory QTL Resources. HUhttp://pga.jax.org/qtl/ UH. Accessed 21 Feb 2012

  4. Hu Z-L, Fritz ER, Reecy JM (2007) AnimalQTLdb: a livestock QTL database tool set for positional QTL information mining and beyond. Nucleic Acids Res 35(database issue):D604–D609

    Article  PubMed  CAS  Google Scholar 

  5. Gramene QTL Database. HUhttp://gramene.agrinome.org/qtl/UH. Accessed 21 Feb 2012

  6. Codd EF (1970) A relational model of data for large shared data banks. Commun ACM 13:377–387

    Article  Google Scholar 

  7. MySQL Workbench 5.2. http://wb.mysql.com/. Accessed 12 May 2010

  8. Hu Z-L, Dracheva S, Jang W-H, Maglott D, Bastiaansen J, Rothschild MF, Reecy JM (2005) A QTL resource and comparison tool for pigs: PigQTLDB. Mamm Genome 16:792–800

    Article  PubMed  Google Scholar 

  9. Aerts J, Burt D, Carre W, DeKoning DJ, Haley C, Hu Z-L, Law A, Reecy J et al. MIQAS—minimum information for QTLs and association studies. http://miqas.sourceforge.net/. Accessed 21 Feb 2012

  10. MySQL. http://www.mysql.com/. Last updated 1 Sep 2010. Accessed 21 Feb 2012

  11. Hu Z-L, Park CA, Fritz ER, Reecy JM (2010) QTLdb: a comprehensive database tool building bridges between genotypes and phenotypes. In: Invited lecture with full paper published electronically on The 9th World Congress on Genetics Applied to Livestock Production (WCGALP), Leipzig, Germany, 1–6 Aug 2010

    Google Scholar 

Further Reading

  • Hernandez MJ (2003) Database design for mere mortals: a hands-on guide to relational database design. Addison-Wesley, Reading, MA, USA

    Google Scholar 

  • Widenius M, Axmark D, Arno K (2002) MySQL reference manual—documentation from the source. O’Reilly Media, O'Reilly Media, Sebastopol, CA, USA

    Google Scholar 

  • Chang E (2003) Practical perl with CGI applications. Addison Wesley, Reading, MA, USA

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Animal Science, Center for Integrated Animal Genomics Iowa State University, 2255 Kildee Hall, Ames, IA, 50011-3150, USA

    Zhi-Liang Hu

  2. Department of Animal Science, Iowa State University, Ames, IA, USA

    James M. Reecy

  3. Departments of Animal Sciences & Dairy Science, UW-Madison, Madison, WI, USA

    Xiao-Lin Wu

Authors
  1. Zhi-Liang Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. James M. Reecy
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiao-Lin Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhi-Liang Hu .

Editor information

Editors and Affiliations

  1. University of California, San Diego, Gilman Drive 9500, La Jolla, 92093, California, USA

    Scott A. Rifkin

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media

About this protocol

Cite this protocol

Hu, ZL., Reecy, J.M., Wu, XL. (2012). Design Database for Quantitative Trait Loci (QTL) Data Warehouse, Data Mining, and Meta-Analysis. In: Rifkin, S. (eds) Quantitative Trait Loci (QTL). Methods in Molecular Biology, vol 871. Humana Press. https://doi.org/10.1007/978-1-61779-785-9_7

Download citation

  • DOI: https://doi.org/10.1007/978-1-61779-785-9_7

  • Published:

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-61779-784-2

  • Online ISBN: 978-1-61779-785-9

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation